Modern electronic communication systems, such as email, have dramatically decreased the costs associated with the distribution of information. As a consequence, the volume of information distributed by modern communication systems has increased significantly. It is now common for a single communication to be transmitted to many thousands (if not millions) of potentially interested recipients.
Distribution lists of contact details (such as email addresses) for recipients interested in particular types of information are now a valuable commodity. These lists may be purchased by content generators and used to target specific sub-sets of potential recipients who are likely to be interested in the information being generated. Alternatively, a content generator may submit information to a distributor and the distributor (who holds the distribution list) may then transmit the information to the potentially interested recipients listed in the distribution list on behalf of the content generator.
For example, a clothing company which will shortly launch a new line of clothing may generate an article announced in the launch. The company submits this article to a distributor who transmits the article, by email for example, to potentially interested recipients listed in a distribution list of recipients who may be interested in the content of that article (e.g. recipients interested in fashion).
This conventional process is, however, flawed.
The distribution lists are often rated on the number of potentially interested recipients listed. Thus, compilers of the distribution lists are inclined to pad the lists with recipients who may, in fact, have little interest in the relevant type of information content.
The distribution list compilers have little motivation to provide quality control for the distribution lists which they produce—for example, the users of the distribution lists may not be the list compliers. Thus, even if individual users provide feedback in response to received information, that feedback does not typically filter back to the list compilers or they may not choose to act on the feedback which they do receive.
Moreover, there is often no mechanism by which the recipients can provide feedback to the distribution list compiler regarding their interests.
Thus, turning back to the article generated by the clothing company, the article may be sent to the journalists at a magazine with a fashion column—these journalists were listed in the distribution list because of the magazine's fashion column. However, a number of those journalists may not be involved in the production of the fashion column of the magazine but may be involved in the production of a food column (for example). Thus, these journalists—who have no interest in the content of the article—will ignore and/or delete the article when it is received.
The fashion company may have selected a particular distributor because of a claim by the distributor regarding the size of the distribution list (and hence the number of recipients) to which that distributor has access. If, however, only 25% of the potentially interested recipients listed in the distribution list are actually potentially interested in the article generated by the clothing company, then that clothing company is effectively paying the distributor to distribute their article to a large number of recipients (75% of the allegedly potentially interested recipients) who will not even consider the content of the article and may, instead, simply delete the article.
Thus, the content generator may find that a different distributor—with access to a different and potentially shorter distribution list—would have provided a better service because more of the potential recipients listed in that distributor's distribution list were actually interested in the content of the article. It is, however, currently impossible for the content generator to obtain any reasonable quality measure for a distribution list which includes an accurate estimation of the number of actually interested recipients who can be targeted.
The inexpensive nature of this form of information distribution through modern communication systems has led to a practice among the distributors of information which is effectively a “shot-gun approach” to the distribution of information. This approach relies on information being distributed to a very large number of recipients in the hope that at least some of those recipients are potentially interested in the information being distributed. The collateral damage associated with this approach is that recipients receive vast quantities of information which may be of no or very little interest.
The large number of unnecessary communications being distributed imposes a significant burden on the infrastructure of the modern communication systems which are being used in this manner.
Moreover, a recipient receiving a large quantity of information of little or no interest, is more likely to miss information which is of interest when compared to a recipient who substantially only receives relevant and interesting information.
Simply establishing whether or not a particular piece of information is relevant may consume a large amount of time for a recipient. This is magnified when the recipient receives a multitude of communications each of which contains information which may (potentially) be of interest and which must be reviewed. Cumulatively, the time expended by recipients reviewing communications can consume large quantities of an organisation's resources.
In addition, the trading of distribution lists can be prejudicial to privacy as contact details for potential recipients are passed from distributor-to-distributor, from content generator-to-content generator and/or from list compiler-to-list compiler without the approval of the potential recipients.
One example of a conventional information filtration system is an unsolicited bulk email filter (a “SPAM filter”). A typical SPAM filter is configured to identify unsolicited bulk email based on information about the transmitter of the email. For example, the internet protocol (IP) address of the sender of an email may be traced by a SPAM filter and the information provided by that trace used by the SPAM filter to determine (within a degree of likelihood) whether or not the email is, in fact, an unsolicited bulk email (i.e. SPAM).
SPAM filtration systems are, however, limited because they identify email as either (i) legitimate or (ii) unsolicited—and unwanted—email. The SPAM filter does not allow for the possibility of one recipient protected by the SPAM filter being interested in the email and another recipient protected by the SPAM filter not being interested in the email. Instead, the SPAM filter applies the same criteria to each email irrespective of the particular interests of the recipient. In other words, SPAM filters typically have no regard for the content of the emails which they are filtering (which may actually be of interest to a recipient).
In the case of the distribution of legitimate information, an information distributor is a legitimate source of information for recipients and a SPAM filter, unless configured by the user to reject all communications from an information distributor, will allow communications from an information distributor irrespective of the information content.
SPAM filters, therefore, provide a coarse email filtration system but are incapable of handling more advanced filtration tasks.
The problems with the prior art are especially prevalent in the field of public relations and in the media industry.
The present invention, therefore, seeks to ameliorate one or more of the problems associated with the prior art.